



'''simple docstring'''






import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version
def  lowerCamelCase__			(		*_A					,     _A = None					,     _A=True					,     _A=2							):
  from .. import __version__

  a		:   List[Any]	  =	take_from
  a		:   List[Any]	  =	()
  if not isinstance(args[0]					,     _A							):
    a		:   List[Any]	  =	(args,)

  for attribute, version_name, message in args:
    if version.parse(version.parse(_A							).base_version							) >= version.parse(_A							):
      raise ValueError(
          f"""The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers'"""
          f""" version {__version__} is >= {version_name}"""							)

    a		:   List[str]	  =	None
    if isinstance(_A					,     _A							) and attribute in deprecated_kwargs:
      values += (deprecated_kwargs.pop(_A							),)
      a		:   List[Any]	  =	f"""The `{attribute}` argument is deprecated and will be removed in version {version_name}."""
    elif hasattr(_A					,     _A							):
      values += (getattr(_A					,     _A							),)
      a		:   int	  =	f"""The `{attribute}` attribute is deprecated and will be removed in version {version_name}."""
    elif deprecated_kwargs is None:
      a		:   int	  =	f"""`{attribute}` is deprecated and will be removed in version {version_name}."""

    if warning is not None:
      a		:   str	  =	warning + ' ' if standard_warn else ''
      warnings.warn(warning + message					,     _A					,     stacklevel=_A							)

  if isinstance(_A					,     _A							) and len(_A							) > 0:
    a		:   int	  =	inspect.getouterframes(inspect.currentframe()							)[1]
    a		:   List[str]	  =	call_frame.filename
    a		:   Tuple	  =	call_frame.lineno
    a		:   List[Any]	  =	call_frame.function
    a  ,      a		:   Union[str, Any]	  =	next(iter(deprecated_kwargs.items()							)							)
    raise TypeError(f"""{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`"""							)

  if len(_A							) == 0:
    return
  elif len(_A							) == 1:
    return values[0]
  return values




'''simple docstring'''






from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       ["""image_processor""", """tokenizer"""]
    lowercase__					=       """BridgeTowerImageProcessor"""
    lowercase__					=       ("""RobertaTokenizer""", """RobertaTokenizerFast""")







    def __init__( self					:    int		,     __snake_case					:    str		,     __snake_case					:    List[str]      ):
      super().__init__(__snake_case		,     __snake_case      )







    def __call__( self					:    int		,     __snake_case					:    Optional[Any]		,     __snake_case					:    Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None		,     __snake_case					:    bool = True		,     __snake_case					:    Union[bool, str, PaddingStrategy] = False		,     __snake_case					:    Union[bool, str, TruncationStrategy] = None		,     __snake_case					:    Optional[int] = None		,     __snake_case					:    int = 0		,     __snake_case					:    Optional[int] = None		,     __snake_case					:    Optional[bool] = None		,     __snake_case					:    Optional[bool] = None		,     __snake_case					:    bool = False		,     __snake_case					:    bool = False		,     __snake_case					:    bool = False		,     __snake_case					:    bool = False		,     __snake_case					:    bool = True		,     __snake_case					:    Optional[Union[str, TensorType]] = None		,     **__snake_case					:    List[Any]		,     ):
      a		:   Optional[int]	  =	self.tokenizer(
          text=__snake_case		,     add_special_tokens=__snake_case		,     padding=__snake_case		,     truncation=__snake_case		,     max_length=__snake_case		,     stride=__snake_case		,     pad_to_multiple_of=__snake_case		,     return_token_type_ids=__snake_case		,     return_attention_mask=__snake_case		,     return_overflowing_tokens=__snake_case		,     return_special_tokens_mask=__snake_case		,     return_offsets_mapping=__snake_case		,     return_length=__snake_case		,     verbose=__snake_case		,     return_tensors=__snake_case		,     **__snake_case		,     )
      # add pixel_values + pixel_mask
      a		:   List[str]	  =	self.image_processor(
          __snake_case		,     return_tensors=__snake_case		,     do_normalize=__snake_case		,     do_center_crop=__snake_case		,     **__snake_case      )
      encoding.update(__snake_case      )

      return encoding







    def      lowercase_			( self					:    int		,     *__snake_case					:    List[str]		,     **__snake_case					:    List[str]      ):
      return self.tokenizer.batch_decode(*__snake_case		,     **__snake_case      )







    def      lowercase_			( self					:    List[str]		,     *__snake_case					:    Tuple		,     **__snake_case					:    Union[str, Any]      ):
      return self.tokenizer.decode(*__snake_case		,     **__snake_case      )







    @property
    def      lowercase_			( self					:    Optional[Any]      ):
      a		:   Optional[Any]	  =	self.tokenizer.model_input_names
      a		:   Union[str, Any]	  =	self.image_processor.model_input_names
      return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names      )      )